Despite the broad application of Machine Learning models as a Service
(M...
Given the great threat of adversarial attacks against Deep Neural Networ...
Adversarial attacks are valuable for evaluating the robustness of deep
l...
The permutation flow shop scheduling (PFSS), aiming at finding the optim...
We present a simple domain generalization baseline, which wins second pl...
Adversarial training has been demonstrated to be one of the most effecti...
Knowledge distillation (KD) has shown its effectiveness for object detec...
Recent studies have shown that detectors based on deep models are vulner...
Adversarial training (AT) methods are effective against adversarial atta...
Extensive evidence has demonstrated that deep neural networks (DNNs) are...
Driven by the ever-increasing requirements of autonomous vehicles, such ...
Transient stability prediction is critically essential to the fast onlin...
Object detection has been widely used in many safety-critical tasks, suc...
Visual object tracking is an important task that requires the tracker to...
Adversarial examples have been demonstrated to threaten many computer vi...